IDEAS home Printed from https://ideas.repec.org/a/gam/jecnmx/v12y2024i2p8-d1365210.html
   My bibliography  Save this article

Biases in the Maximum Simulated Likelihood Estimation of the Mixed Logit Model

Author

Listed:
  • Maksat Jumamyradov

    (Department of Economics, University of South Florida, Tampa, FL 33620, USA)

  • Murat Munkin

    (Department of Economics, University of South Florida, Tampa, FL 33620, USA)

  • William H. Greene

    (Department of Economics, University of South Florida, Tampa, FL 33620, USA)

  • Benjamin M. Craig

    (Department of Economics, University of South Florida, Tampa, FL 33620, USA)

Abstract

In a recent study, it was demonstrated that the maximum simulated likelihood (MSL) estimator produces significant biases when applied to the bivariate normal and bivariate Poisson-lognormal models. The study’s conclusion suggests that similar biases could be present in other models generated by correlated bivariate normal structures, which include several commonly used specifications of the mixed logit (MIXL) models. This paper conducts a simulation study analyzing the MSL estimation of the error components (EC) MIXL. We find that the MSL estimator produces significant biases in the estimated parameters. The problem becomes worse when the true value of the variance parameter is small and the correlation parameter is large in magnitude. In some cases, the biases in the estimated marginal effects are as large as 12% of the true values. These biases are largely invariant to increases in the number of Halton draws.

Suggested Citation

  • Maksat Jumamyradov & Murat Munkin & William H. Greene & Benjamin M. Craig, 2024. "Biases in the Maximum Simulated Likelihood Estimation of the Mixed Logit Model," Econometrics, MDPI, vol. 12(2), pages 1-16, March.
    • Handle: RePEc:gam:jecnmx:v:12:y:2024:i:2:p:8-:d:1365210
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2225-1146/12/2/8/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2225-1146/12/2/8/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ossama Elshiewy & German Zenetti & Yasemin Boztug, 2017. "Differences Between Classical and Bayesian Estimates for Mixed Logit Models: A Replication Study," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 470-476, March.
    2. Marco A. Palma & Dmitry V. Vedenov & David Bessler, 2020. "The order of variables, simulation noise, and accuracy of mixed logit estimates," Empirical Economics, Springer, vol. 58(5), pages 2049-2083, May.
    3. William Greene & David Hensher, 2010. "Does scale heterogeneity across individuals matter? An empirical assessment of alternative logit models," Transportation, Springer, vol. 37(3), pages 413-428, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Elin Spegel & Kristina Ek, 2022. "Valuing the Impacts of Landslides: A Choice Experiment Approach," Economics of Disasters and Climate Change, Springer, vol. 6(1), pages 163-181, March.
    2. Kassie, Girma T. & Zeleke, Fresenbet & Birhanu, Mulugeta Y. & Scarpa, Riccardo, 2020. "Reminder Nudge, Attribute Nonattendance, and Willingness to Pay in a Discrete Choice Experiment," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304208, Agricultural and Applied Economics Association.
    3. Chavez, Daniel E. & Palma, Marco A. & Nayga, Rodolfo M. & Mjelde, James W., 2020. "Product availability in discrete choice experiments with private goods," Journal of choice modelling, Elsevier, vol. 36(C).
    4. David Hensher & John Rose & Zheng Li, 2012. "Does the choice model method and/or the data matter?," Transportation, Springer, vol. 39(2), pages 351-385, March.
    5. Line Bjørnskov Pedersen & Julie Riise & Arne Risa Hole & Dorte Gyrd-Hansen, 2014. "GPs' shifting agencies in choice of treatment," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 750-761, March.
    6. ILes, Richard, 2017. "Government Doctor Absenteeism And Its Effects On Consumer Demand In Rural North India," Working Papers 2018-9, School of Economic Sciences, Washington State University, revised 12 2018.
    7. Hensher, David A., 2012. "Accounting for scale heterogeneity within and between pooled data sources," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 480-486.
    8. Bartczak, Anna, 2015. "The role of social and environmental attitudes in non-market valuation," Forest Policy and Economics, Elsevier, vol. 50(C), pages 357-365.
    9. Arne Hole & Julie Kolstad, 2012. "Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment," Empirical Economics, Springer, vol. 42(2), pages 445-469, April.
    10. Arouna, Aminou & Adegbola, Patrice Y. & Raphael, Babatunde & Diagne, Aliou, 2015. "Contract farming preferences by smallholder rice producers in Africa: a stated choice model using mixed logic," 2015 Conference, August 9-14, 2015, Milan, Italy 210957, International Association of Agricultural Economists.
    11. Laura Enthoven & Goedele Van den Broeck, 2021. "Promoting Food Safety in Local Value Chains: The Case of Vegetables in Vietnam," Sustainability, MDPI, vol. 13(12), pages 1-17, June.
    12. Catalina M. Torres Figuerola & Nick Hanley & Sergio Colombo, 2011. "Incorrectly accounting for taste heterogeneity in choice experiments: Does it really matter for welfare measurement?," CRE Working Papers (Documents de treball del CRE) 2011/1, Centre de Recerca Econòmica (UIB ·"Sa Nostra").
    13. David Boto‐García & Antonio Alvarez & José Baños, 2021. "Modelling heterogeneous preferences for nature‐based tourism trips," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1625-1653, December.
    14. Weber, Matthew A. & Meixner, Thomas & Stromberg, Juliet C., 2016. "Valuing instream-related services of wastewater," Ecosystem Services, Elsevier, vol. 21(PA), pages 59-71.
    15. Chen, Tiantian & Fu, Xiaowen & Hensher, David A. & Li, Zhi-Chun & Sze, N.N., 2022. "Air travel choice, online meeting and passenger heterogeneity – An international study on travellers’ preference during a pandemic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 439-453.
    16. Holte, Jon Helgheim & Kjaer, Trine & Abelsen, Birgit & Olsen, Jan Abel, 2015. "The impact of pecuniary and non-pecuniary incentives for attracting young doctors to rural general practice," Social Science & Medicine, Elsevier, vol. 128(C), pages 1-9.
    17. Puckett, Sean M. & Rose, John M. & Bain, Stuart, 2012. "Modelling heterogeneity in scale directly: implications for estimates of influence in freight decision-making groups," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 50, pages 1-2.
    18. Hess, Stephane & Stathopoulos, Amanda, 2013. "Linking response quality to survey engagement: A combined random scale and latent variable approach," Journal of choice modelling, Elsevier, vol. 7(C), pages 1-12.
    19. Didier Nibbering, 2023. "A High-dimensional Multinomial Logit Model," Monash Econometrics and Business Statistics Working Papers 19/23, Monash University, Department of Econometrics and Business Statistics.
    20. Fecke, Wilm & Danne, Michael & Mußhoff, Oliver, 2018. "E-commerce in agriculture: The case of crop protection product purchases in a discrete choice experiment," DARE Discussion Papers 1803, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jecnmx:v:12:y:2024:i:2:p:8-:d:1365210. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.